
LSTM/GRU: RNN models trained on the raw input.

BRITS* [1]}: a bidirectional RNN with a built-in imputation component for handling missingness in the input The inputs to BRITS are down-sampled by a factor of 20. The original raw inputs cause slow training and the performance is sub-optimal compared to model trained with down-sampled inputs.

GRU-D* [2]}: a GRU model with a built-in imputation component for handling missingness in the input data. The input is also down-sampled by a factor of 20.

Latent-ODE [3]}: a latent neural ordinal differential equations model for irregular time-series input.

